by Fronetics | Sep 19, 2019 | Blog, Data/Analytics, Marketing, Marketing Automation, Supply Chain
In a highly competitive B2B landscape, AI can be the strategic advantage your brand needs. Here’s everything you need to know about AI for marketing.
Highlights:
- AI enables predictive analysis – the ability to look at a large set of data and predict what steps to take to reach a desired outcome.
- Social listening powered by AI gives marketers key insights into brand perception and audience reaction.
- When considering purchasing an AI technology for marketing, consider if it includes its own Big Data source.
When we think about artificial intelligence (AI), it’s often with a twinge of unease. Whether it’s pop culture telling us that robots will take over at their earliest opportunity, or fears of human labor being replaced with machines, AI is a complex, controversial, and even mysterious topic. But when it comes to the applications of AI for marketing, there’s actually a lot to celebrate.
It’s important for marketers not only to have a thorough understanding of the uses of AI for marketing, but to be aware of industry trends, and how to determine investment to maximize ROI.
What is AI for marketing?
While it’s not necessary for marketers to be artificial intelligence and robotics experts, it’s beneficial to have a functional understanding of the technology that enables AI for marketing. In a general sense, the term “AI” refers to the area of computer science that enables the creation of software and machines that possess what we think of as intelligence. That is, they are able to work, react, and learn without being specifically programmed for each task.
AI is enabled by data science, “the practice of organizing and analyzing massive amounts of data.” When it comes to marketing, AI can be thought of as an extension and development of marketing automation. Essentially, AI for marketing is software that collects, analyzes, and reacts to large amounts of data, with increasing levels of sophistication.
According to content intelligence expert Bart Frischknecht, of Vennli, AI for marketing can be categorized in one of two ways.
- Recommending: This type of marketing software “predicts which action will have the most positive outcome in order to recommend a next step in a series of events.” Frischknecht describes these recommendations as “stepping stones on the way to fully automating a given task.”
- Automating: Software that automates is a furtherance of software that recommends. For a task to be automated, it needs to be “routine and repeatable, the goal needs to be specific, and the steps to achieve that goal must follow an exact set of rules.”
Think of data as the fuel that powers AI for marketing. As we gather more and more data, and devise increasingly sophisticated analytical methods, the possibilities for intelligent automation in marketing will continue to expand.
5 examples of AI for marketing
1) Data filtering and analysis
At Fronetics, we’ve advocated for a data-driven approach to marketing since our founding. For marketers, data is the most powerful strategic weapon in your arsenal, and AI is sharpening it even further. AI software can consolidate large amounts of data, and analyze it to determine patterns and trends.
2) Social listening
Social listening, also known as social monitoring, is the process of observing and examining social media, to identify and access what is being said about your brand. Social listening gives marketers valuable market intelligence, prospect insight, tone awareness, and competitive advantage.
Current AI software lets marketers not only engage in sophisticated social monitoring, but it also enables “sentiment analysis,” automatically generating a report of the overall attitude of your audience and perception of your brand.
3) Predictive analysis
Beyond simply filtering and analyzing data, AI for marketing goes a crucial step further: predictive analysis, the practice of applying the information extracted from data sets to predict a future outcome or trend.
This revolutionary capability of AI can be used to analyze buyer purchase behavior, for example, and determine when and how to distribute certain types of content. Social media scheduling tools, for instance, use predictive analysis to suggest the optimal times to share content.
4) Audience targeting and segmentation
As B2B buyers increasingly come to expect personalization at all stages of the buyer’s journey, it can be a challenge for marketers to deliver. However, AI makes personalization possible at a large scale, drawing on data to segment and categorize audiences.
The limits of the specificity of this segmentation are determined only by the amount of data available. In other words, the more data, the more the AI software can instantly segment a contact list and deliver personalized correspondence.
5) Chatbots
One of the most ubiquitous examples of AI for marketing, chatbots are computer programs that simulate human conversation using auditory or textual methods. Chatbots communicate with buyers within a messaging app, like Facebook messenger.
3 questions to ask when considering an investment in AI for marketing
While the possibilities of AI for marketing are virtually endless, the reality for most companies is that marketing budgets are not. When considering an investment in any technology, including AI, maximizing ROI should be top of mind. Frischknecht suggests that marketers ask the following three questions when considering an investment in AI for marketing:
- Which marketing task will this technology automate, and will doing so alleviate a significant burden for marketing staff?
- Does purchase of the tech include its own Big Data source, or do I need to provide all the data? If the latter, do I have adequate data, and can I connect my data source to the tech?
- What evidence exists of the tech making good recommendations or automating one of my tasks.
AI is revolutionizing marketing. Investing intelligently in these technologies can provide critical market insights, data processing capabilities, and predictive analysis.
Related posts:
by Fronetics | Sep 17, 2019 | Big Data, Blog, Data/Analytics, Internet of Things, Robotics & Automation, Supply Chain
Machine learning is shaping the future of supply chain and logistics management, improving accuracy, speed, scale, and more. Here’s how.
Highlights:
- Machine learning refers to an application of artificial intelligence that lets systems learn and improve automatically based on experience.
- Experts predict that 95% of supply chain planning vendors will rely on supervised and unsupervised machine learning for their solutions by 2020.
- When paired with the Internet of Things, machine learning can provide cost savings around $6 million per year.
When it comes to the future of the supply chain, machine learning is one of the most exciting applications of artificial intelligence (AI) technology out there today. Machine learning is a mode of data analysis that provides systems with the ability to learn and improve automatically from experience, without being specifically programmed.
Gartner recently projected that by 2020, 95% of supply chain planning vendors will rely on supervised and unsupervised machine learning for their solutions. Furthermore, it isn’t just expert predictions that demonstrate the impact and potential of machine learning for the supply chain. Amazon, for example, is using machine learning to improve accuracy, speed, and scale for its Kiva robotics, and DHL relies on machine learning to power its Predictive Network Management system.
So, what is it about machine learning that makes it ideally suited to meet the challenges commonly faced by supply chain companies? The answer lies in the fact that machine learning algorithms are brilliant at detecting patterns, anomalies, and predictive insights. This makes it the ideal technology to help supply chain companies forecast error rates, reduce costs, improve demand planning productivity, and increase on-time shipments.
Here’s how these remarkable technologies are already revolutionizing supply chain management.
7 ways machine learning is improving supply chain management
1) Logistic solutions
Particularly when it comes to resource scheduling systems, machine learning algorithms are driving the next generation of logistics technologies. An April 2019 report from McKinsey predicts that “machine learning’s most significant contributions will be in providing supply chain operators with more significant insights into how supply chain performance can be improved, anticipating anomalies in logistics costs and performance before they occur.”
2) Internet of Things
The Internet of Things (IoT)’s sensors, intelligent transport systems, and traffic data generate a tremendous variation in data sets. Machine learning has the potential to deliver increased value by analyzing these data sets, thereby optimizing logistics and ensuring that materials arrive timely.
Additionally, machine learning can reduce logistics costs by uncovering patterns in track-and-trace data captured through IoT-enabled sensors. A December 2018 study by Boston Consulting Group determined that pairing machine learning (specifically Blockchain) with the IoT can contribute to cost savings of $6 million per year.
3) Preventing privileged credential abuse
A recent article in Forbes points to privileged credential abuse as “the leading cause of security breaches across global supply chains.” Machine learning can prevent these abuses by verifying the identity of anyone requesting access, as well as the context of the request and, most importantly, the risk associated with the access environment.
4) Reducing fraud potential
In addition to reducing risk and improving product and process quality, machine learning can reduce the potential for fraud in the supply chain. For example, machine learning startup Inspectorio is a solution to the problems “that a lack of inspection and supply chain visibility creates, focusing on how they can solve them immediately for brands and retailers.” Their algorithm provides insights that instantaneously reduce the risk of fraud.
5) Reducing forecast errors
According to a recent report from Digital/McKinsey, “Lost sales due to products not being available are being reduced up to 65% through the use of machine learning-based planning and optimization techniques.” The same report observes that “inventory reductions of 20 to 50% are being achieved today when machine learning-based supply chain management systems are used.”
6) Detecting inconsistent supplier quality levels
Machine learning can help manufacturers combat one of the biggest problems they face today, namely a lack of consistent quality and delivery performance from suppliers. These technologies can quickly detect and address errors, as well as determine highest and lowest performing suppliers.
7) Preventative maintenance
Preventative maintenance is a tremendous strategic asset for the supply chain. And, when paired with machine learning, it “allows for better prediction and avoidance of machine failure by combining data from the advanced IoT sensors and maintenance logs as well as external sources,” according to the same Digital/McKinsey study mentioned above. Not only that, “asset productivity increases of up to 20% are possible, and overall maintenance costs may be reduced by up to 10%.”
The bottom line: machine learning is reinventing supply chain management
Not only has machine learning already realized tremendous value for the supply chain, but the very nature of this technology means that the possibilities are virtually endless. Algorithms continue to become more sophisticated, and, as new challenges arise, machine learning grows and evolves to meet them.
Related posts:
by Fronetics | Jun 4, 2019 | Blog, Data/Analytics, Marketing
There is a lot marketers can learn from data collection that can be helpful in the buyer’s journey. However, with all this information comes challenges. Here’s how to overcome the challenges of data-driven digital marketing.
Highlights:
- Data is a key component in driving decisions when it comes to digital strategies.
- Try using analytics tools that take into account all of your data activity and tracks it through all of your channels and platforms.
- The key to using data to optimize your marketing efforts is the ability to collect and analyze the data.
Video transcript:
I’m Jennifer Yim, the Director of Strategy here at Fronetics, and today we’re going to be talking about how to overcome the challenges of data-driven digital marketing.
Data is a key component in driving decisions when it comes to digital strategies. And there are a lot of things marketers can learn from data collection. Those can be helpful in identifying opportunities along the buyer’s journey. But all this information comes with its own set of challenges.
Here are the three of the biggest challenges of a data-driven strategy and how to overcome them.
1. Finding the right data and KPIs
There is no point in tracking data if it can’t be used to serve a purpose. Digital marketers need to give the data meaning by utilizing the numbers they’re collecting.
Once you finalize a strategy, start tracking the specific data points that contribute to those KPIs. Some of the most important KPIs are website traffic, engagement rates, and conversions. And remember, time is a key factor in analyzing data.
2. Having the right platforms and tools
As a marketer, you need the right tools to determine what’s working and what isn’t. Try using analytics tools that takes in all your data activity and tracks it through all of your channels and platforms. This will give you a full picture of what is happening throughout the buyer’s journey and will also help you make more informed decisions about tweaking your strategies.
3. Bringing it all together
The key to using data to optimize your marketing efforts is the ability to collect and analyze the data. Keep consistency in how you report and organize your results and use this insight to drive your marketing strategy. What’s working? What can you improve? Constantly be working to make your marketing plan to align with your top performing digital marketing efforts.
You can learn more at Fronetics.com.
Related posts:
by Fronetics | May 29, 2019 | Blog, Content Marketing, Data/Analytics, Marketing
These Google Analytics reports are crucial to understanding the visitors who are browsing your website and how you are more likely to get them to convert.
Highlights:
- Audience reports tell you who is visiting your website.
- Acquisition reports convey how are users getting to your website.
- Behavior reports show what visitors are doing on your website.
(Made with Canva)
Your website is your best opportunity to convert digital prospects into leads. But how can you learn who is browsing your website and what they are doing while they’re there? Most importantly, how can you get more of them to convert? Here’s where tools like Google Analytics can help.
Google Analytics is one of if not THE most comprehensive analytics tools available to digital marketers. But it can be very overwhelming if you don’t know how to navigate it. So, we’ve come up with the 3 Google Analytics reports you should be running if you want to understand how to get more visitors to convert on your website.
But, first, let’s start with the basics.
Understanding Google Analytics
At a fundamental level, Google Analytics helps you understand and make decisions based on the traffic that comes to your website. This free tool is a powerhouse that uses a JavaScript code to collect data surrounding how users interact with your website. It then processes that data and generates customizable reports for you within the platform.
[bctt tweet=”This free tool is a powerhouse that uses a JavaScript code to collect data surrounding how users interact with your website. It then processes that data and generates customizable reports for you within the platform.” username=”Fronetics”]
I should say: the data you gain from Google Analytics is all the richer if you begin by setting up Goals on the platform. This way, Google Analytics can go to work for you, measuring how well your website is fulfilling your specific objectives. If you start by properly setting and configuring your goals, Google Analytics can provide you with critical information that’s specific to your strategy. Of course, you can always add to or adjust your goals, as you collect data.
Getting the most out of Google Analytics can empower you to make improvements to your website based on the data it collects for you. The more information you have about your site and its traffic, the more you can make adjustments to meet your objectives. Furthermore, the insights you gain from your metrics can help shape future objectives, to improve user experience on your site.
3 Google Analytics reports that are key to getting the most out of the platform
Using Google Analytics, you can gain insight into some of the most important questions surrounding user engagement with your website. In particular, these 3 reports are helpful in getting the most useful data for understanding lead conversion opportunities:
- Audience reports: Who is visiting your website?
- Acquisition reports: How are users getting to your website?
- Behavior reports: What are website visitors doing on your website?
Here’s what you need to know about each report.
1) Audience reports
As you create and publish content on your website, you need to know who’s reading/watching/viewing/listening to it. With Google Analytics, you can get information about your audience such as age, location, gender, interests, and other behavior.
As users are increasingly engaging with websites on mobile devices, we often encourage clients to monitor the Mobile report as well as other audience demographics. This report shows you what percentage of your audience comes from a mobile device, as compared to a desktop or tablet. You need this information, particularly because mobile device users tend to have different behavior and goals from those on desktops. If your traffic is heavily mobile, your site needs to be optimized for these visitors.
We also encourage clients to make use of Google Analytics’ audience benchmarking reports. These reports allow you to compare your results with aggregated industry data, giving you the context you need to set targets. Benchmarking can also give you insights into industry-wide trends and help you determine how you’re doing as compared to your competitors.
2) Acquisition reports
Knowing how visitors are getting to your website will empower you not only to improve your site, but to make strategic decisions surrounding your other digital channels. Google Analytics offers acquisition reports that provide insight into where your visitors originated from. Users may be finding your website through search engines, social networks, website referrals, and more.
Use the Acquisition Overview to get a quick overview of the top channels that are funneling visitors to your website. You can also see associated acquisition, behavior, and conversion details for each of these channels. If you have your Google Analytics Goals in place, the Acquisitions Overview report will display how well each channel is driving conversions.
Next, take a deeper dive in the Channels section, which gives you rich information about each of your channels. For example, if you click on the “Organic Search” channels, Google Analytics takes you to the Keywords report, which lets you know how you’re faring with specific search queries. Clicking the “Direct” channel will take you to the top landing pages for direct site visitors, and “Social” shows you your top-referring social networks.
3) Behavior reports
Once visitors are on your site, what are they doing there? If you’re getting the most out of Google Analytics, you can see how visitors move through your site and interact with your content – and, in turn, you can be strategic about optimizing your website for conversions.
Start with the Behavior Overview. Here, you’ll find a graph of the amount of traffic your website receives, as well as additional metrics such as Pageviews, Average Time on Page, Bounce Rate, and more.
For more insight, the Behavior Flow report shows you the path users typically take on your website. You can see the first page they view, all the way to the final page they typically visit before exiting your site. Here, you’re getting a visual of how long visitors stay on your website — and learn a bit about why they leave.
The bottom line: Google Analytics reports help you optimize your website
Data empowers you to make informed decisions and tailor your strategies to meet your objectives. Not only that, data can help you determine your objectives in the first place. Google Analytics is perhaps the most robust tool out there for gathering information and insights into essentially every aspect of your website. Make sure you’re making use of it.
What Google Analytics reports have you found most helpful?
Related posts:
by Fronetics | May 21, 2019 | Blog, Content Marketing, Data/Analytics, Logistics, Marketing, Supply Chain
Supply chain companies are increasingly recognizing the need to align sales and marketing teams through the use of analytics.
Highlights:
- Sales and marketing alignment can be aided by analytics tools.
- A content audit can ensure sales has relevant material for every stage of the buyer’s journey.
- Digital Asset Management Software acts as a unified repository for content and analytics data.
Often, when we first talk to prospects about digital marketing, their sales teams start to get the jitters. There’s a big misperception out there that inbound marketing is bound to make sales teams obsolete – but this couldn’t be further from the truth. In fact, when companies take steps to align sales and marketing teams, their efforts start to pay off in big ways.
We’ve written a lot about how to align sales and marketing, as well as the dangers that crop up when companies haven’t synchronized these departments. That’s not to say that it’s an easy task. In fact, HubSpot’s 2018 State of Inbound report found that a mere 22% of companies report that their sales and marketing relationship is tightly aligned. Increasingly, supply chain companies are finding success using analytics tools to meet the challenges of aligning sales and marketing teams.
Understand your target audience
If you’re on the marketing side, you probably have a picture of your target audience, including multiple specific buyer personae. But how familiar is your sales team with this information? Chances are, sales has knowledge about your target audience that is based as much on experience as it is on the goals your marketing department created.
If the lines of communication aren’t clear when it comes to understanding your target audience, you’re shortchanging both marketing and sales. The sales department needs clear and complete communication from marketing about the type of buyers being targeted. Meanwhile, the knowledge that sales personnel will have accrued from their on-the-ground experience can help shape future marketing efforts.
To align sales and marketing in their understanding of your target audience, web analytics tools like Google Analytics are extremely beneficial. Use analytics to track user interaction with all your digital assets and build accurate personae that are data-driven. Ideally, analytics can validate and enhance the knowledge that sales teams have built.
Align sales and marketing with content that enables sales in a digital space
One of the most frequent complaints sales teams voice is that they lack relevant materials from marketing. And on the other side of the coin, marketing departments often report that sales teams aren’t clear about their needs, nor do they use the materials they’ve provided.
To get everyone on the same page, perform a content audit to determine which of your existing content matches with each target buyer persona, as well as what content will be most useful to your sales team at each stage of the buyer’s journey. Next, put some analytics in place. You need to know how your content is performing not just from a lead-generation perspective, but from the standpoint of closing deals.
To help you develop a process for evaluating the success of your content and soliciting and incorporating feedback from sales, Digital Asset Management Software is a great resource. Tools like Canto or Bynder can be a synchronized, discoverable repository of marketing assets and their function for sales, as well as help you keep track of your analytics.
Final thoughts
As supply chain companies are increasingly recognizing the need for sales and marketing teams that work in tight alignment, analytics are an invaluable resource for synchronizing efforts across departments. And the possibilities are continuing to expand for what analytics, including artificial intelligence, can do.
Keeping the lines of communication open, and sharing analytics data will help lead to accurate, data-driven buyer personas and an optimally functioning sales team.
Related posts:
by Fronetics | Dec 17, 2018 | Blog, Content Marketing, Data/Analytics, Marketing
Implementing automation can help supply chain marketers become more efficient and more successful in earning and converting leads. Here are our most-viewed automation posts of the year.
Automation is changing the way supply chain marketers do their job. When properly executed, automation can drive efficiency and reduce time spent on repetitive tasks, freeing up marketers to focus on other priorities.
Marketing automation is the process of using software to complete repetitive marketing tasks designed to nurture sales leads, personalize marketing messages and content, and — in the process — save marketers time and effort. Supply chain marketers are using marketing automation to streamline processes and increase qualified leads.
Jumping into marketing automation can be overwhelming. Utilizing the right software and knowing where to implement automation into your marketing processes will help nurture leads and get you back to more pressing tasks.
[bctt tweet=”Utilizing the right software and knowing where to implement automation into your marketing processes will help nurture leads and get you back to more pressing tasks.” username=”Fronetics”]
Here are our top automation posts from 2018 that define how automating your marketing processes can help your efforts.
Top 5 automation posts 2018
1. Our 6 Favorite Marketing Automation Tools for Supply Chain and Logistics Marketers
The term “marketing automation” refers to a variety of tools used to automate the process of personalizing leads’ interactions with your business. The sheer variety of these tools can sometimes be overwhelming — so we’ve pulled a few of our favorites in the categories of email workflows, social media scheduling tools, and customer relationship management. Read full post
2. Increase Leads by 451% through Marketing Automation
Automation is changing today’s supply chain, and not just because robots and autonomous vehicles are scooting around warehouse floors. Supply chain marketers can use automation to drive efficiency and improve our success rates. Read full post
3. Marketing Automation: Social Media Scheduling Tools
Managing your business’ social media accounts might sound like a simple task — a fun one, even. But once it falls on your plate, it won’t take you long to realize: it’s a lot of work. Social media scheduling tools can make your job much easier — and improve your bottom line. Here are some of our favorite tools and some helpful tips for using them. Read full post
4. 5 Tips for Using Automation in Email Marketing
Marketing automation can help you provide more personalized experiences for your prospects through email. It can also save you a significant amount of time, as you won’t have to create individual emails each time a particular prospect takes a particular action.
But not everything can, or should, be automated or scheduled in advance. As you begin to incorporate automation in email marketing, here are 5 tips to get you started. Read full post
5. Marketing Automation: CRM (Customer Relationship Management)
Integrating marketing automation into your CRM strategy can improve efficiency, streamline workflows, and make communications more consistent. Here are a few examples of how CRM and marketing automation can work in tandem. Read full post
Related posts:
